Fine-tuning large neural language models for biomedical natural language processing

Large neural language models have transformed modern natural language processing (NLP) applications. However, fine-tuning such models for specific tasks remains challenging as model size increases, especially with small labeled datasets, which are common in biomedical NLP. We conduct a systematic st...

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Detalles Bibliográficos
Autores principales: Tinn, Robert, Cheng, Hao, Gu, Yu, Usuyama, Naoto, Liu, Xiaodong, Naumann, Tristan, Gao, Jianfeng, Poon, Hoifung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140607/
https://www.ncbi.nlm.nih.gov/pubmed/37123444
http://dx.doi.org/10.1016/j.patter.2023.100729

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140607/
https://www.ncbi.nlm.nih.gov/pubmed/37123444
http://dx.doi.org/10.1016/j.patter.2023.100729

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